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Data Extraction for the Oracle Warehouse

Oracle Tips by Burleson Consulting

High Performance Data Warehousing

Data Extraction For The Oracle Warehouse 

As we know, most data warehouses are loaded in batch mode after the online system has been shut down. In this sense, a data warehouse is bimodal, with a highly intensive loading window, and an intensive read-only window during the day. Because many data warehouses collect data from non-relational databases such as IMS or CA-IDMS, no standard methods for extracting data are available for loading into a warehouse. However, there are a few common techniques for extracting and loading data, including:

* Log “sniffing”--Applying archived redo logs from the OLTP system to a data warehouse.

* Using update, insert, and delete triggers--Firing-off a distributed update to a data warehouse.

* Using snapshot logs to populate the data warehouse--Using log files to update replicated table changes.

* Running nightly extract/load programs--Using extracts to retrieve operational data and load it into a warehouse.

For details about data extraction and loading of Oracle warehouses, see Chapter 11, Oracle Data Warehouse Utilities.

Data Aggregation

Several methods can be used to aggregate data within OLAP servers. As you can see in Figure 1.16, this method extracts data from the relational engine and summarizes the data for display. Another popular method pre-aggregates the data and keeps the summarized data ready for retrieval.

Figure 1.16 Aggregation and OLAP servers.

For details about data aggregation in Oracle warehouses, see Chapter 10, Aggregating Data For Oracle Warehouses.

This is an excerpt from "High Performance Data Warehousing", copyright 1997.
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